Williams-Sonoma, Inc. (WSM)
founded in 1956, williams-sonoma, inc. is the premier specialty retailer of high-quality products for the kitchen and home in the united states. our family of brands are williams-sonoma, pottery barn, pottery barn kids, pbteen, west elm, williams-sonoma home, rejuvenation, and mark and graham. these brands are among the best known and most respected in the industry. we offer beautifully-designed, stylish and functional products for every area of the home, including the kitchen, living room, bedroom, home office, closet, laundry room and even outdoor spaces. we've seen some big changes since our first brick-and-mortar store opened more than half of a century ago. what hasn't changed is our passion for high-quality products, functional design, outstanding customer service, and enhancing the lives of our customers and the communities where we operate. today, we're a multi-brand, multi-channel, global enterprise supported by state-of-the-art technology and some of the most talented teams i
Stock Price Trends
Stock price trends estimated using linear regression.
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Key facts
- The primary trend is decreasing.
- The decline rate of the primary trend is 18.66% per annum.
- WSM price at the close of November 28, 2023 was $184.02 and was higher than the top border of the primary price channel by $56.18 (43.95%). This indicates a possible reversal in the primary trend direction.
- The secondary trend is increasing.
- The growth rate of the secondary trend is 105.44% per annum.
- WSM price at the close of November 28, 2023 was higher than the top border of the secondary price channel by $2.90 (1.60%).
- The direction of the secondary trend is opposite to the direction of the primary trend. This indicates a possible reversal in the direction of the primary trend.
Linear Regression Model
Model equation:
Yi = α + β × Xi + εi
Top border of price channel:
Exp(Yi) = Exp(a + b × Xi + 2 × s)
Bottom border of price channel:
Exp(Yi) = Exp(a + b × Xi – 2 × s)
where:
i - observation number
Yi - natural logarithm of WSM price
Xi - time index, 1 day interval
σ - standard deviation of εi
a - estimator of α
b - estimator of β
s - estimator of σ
Exp() - calculates the exponent of e
Primary Trend
Start date:
End date:
a =
b =
s =
Annual growth rate:
Exp(365 × b) – 1
= Exp(365 × ) – 1
=
Price channel spread:
Exp(4 × s) – 1
= Exp(4 × ) – 1
=
March 18, 2021 calculations
Top border of price channel:
Exp(Y)
= Exp(a + b × X + 2 × s)
= Exp(a + b × + 2 × s)
= Exp( + × + 2 × )
= Exp()
= $
Bottom border of price channel:
Exp(Y)
= Exp(a + b × X – 2 × s)
= Exp(a + b × – 2 × s)
= Exp( + × – 2 × )
= Exp()
= $
July 24, 2023 calculations
Top border of price channel:
Exp(Y)
= Exp(a + b × X + 2 × s)
= Exp(a + b × + 2 × s)
= Exp( + × + 2 × )
= Exp()
= $
Bottom border of price channel:
Exp(Y)
= Exp(a + b × X – 2 × s)
= Exp(a + b × – 2 × s)
= Exp( + × – 2 × )
= Exp()
= $
Secondary Trend
Start date:
End date:
a =
b =
s =
Annual growth rate:
Exp(365 × b) – 1
= Exp(365 × ) – 1
=
Price channel spread:
Exp(4 × s) – 1
= Exp(4 × ) – 1
=
May 1, 2023 calculations
Top border of price channel:
Exp(Y)
= Exp(a + b × X + 2 × s)
= Exp(a + b × + 2 × s)
= Exp( + × + 2 × )
= Exp()
= $
Bottom border of price channel:
Exp(Y)
= Exp(a + b × X – 2 × s)
= Exp(a + b × – 2 × s)
= Exp( + × – 2 × )
= Exp()
= $
October 25, 2023 calculations
Top border of price channel:
Exp(Y)
= Exp(a + b × X + 2 × s)
= Exp(a + b × + 2 × s)
= Exp( + × + 2 × )
= Exp()
= $
Bottom border of price channel:
Exp(Y)
= Exp(a + b × X – 2 × s)
= Exp(a + b × – 2 × s)
= Exp( + × – 2 × )
= Exp()
= $